Loading and Visualization#

In this section, we illustrate how to load and visualize the pseudoPAGES2k dataset with cfr.

Required data to complete this tutorial:

pseudoPAGES2k: ppwn_SNRinf_rta.nc

[1]:

%load_ext autoreload
%autoreload 2

import cfr
import xarray as xr

import os
os.chdir('/glade/u/home/fengzhu/Github/cfr/docsrc/notebooks/')

Load the pseudoPAEGS2k dataset with `cfr`#

The cfr.ProxyDatabase class comes with a .load_nc() method that can help us load a proxy database from a netCDF file following the certain format shown above:

[4]:

# load the pseudoPAGES2k database from a netCDF file
pdb = cfr.ProxyDatabase().load_nc('./data/ppwn_SNRinf_rta.nc')

Visualize the pseudoPAGES2k dataset#

Once the netCDF file is loaded as a cfr.ProxyDatabase, we can easily visualize the dataset with the .plot() method:

[5]:

fig, ax = pdb.plot()

../_images/notebooks_pp2k-pdb-load-viz_9_0.png

We may also plot map along with the count of the records:

[7]:

fig, ax = pdb.plot(plot_count=True)

../_images/notebooks_pp2k-pdb-load-viz_11_0.png

Since the dataset starts from 850 AD, we may adjust the x-axis utilizing the matplotlib methods:

[6]:

fig, ax = pdb.plot(plot_count=True)
ax['count'].set_xlim(800, 2000)

[6]:

(800.0, 2000.0)

../_images/notebooks_pp2k-pdb-load-viz_13_1.png

Access and visualize a specific record#

A specific record can be accessed by its proxy ID:

[8]:

pobj = pdb['NAm_001']
pobj

[8]:

<cfr.proxy.ProxyRecord at 0x2abc9a7c58b0>

This returned object is defined by cfr.ProxyRecord, which comes with several attributes such as: - time: the time axis - value: the value axis - lat: the latitude of the site - lon: the longitude of the site - (… other metadata)

For instance, to access the record series:

[9]:

print('time axis:', pobj.time)
print('value axis:', pobj.value)

time axis: [ 850.  851.  852. ... 2000. 2001. 2002.]
value axis: [1.0390625 0.796875  0.796875  ... 0.75      0.453125  0.78125  ]

Now that we have the cfr.ProxyRecord object, we can easily visualize the record utilizing the .plot() method:

[10]:

fig, ax = pobj.plot()

../_images/notebooks_pp2k-pdb-load-viz_19_0.png

We may slice the record to zoom in and out. For instance, let us check the instrumental period:

[11]:

fig, ax = pobj.slice([1850, 2000]).plot()

../_images/notebooks_pp2k-pdb-load-viz_21_0.png

We may also slice with a shortcut using strings of years:

[12]:

fig, ax = pobj['1850':'2000'].plot()

../_images/notebooks_pp2k-pdb-load-viz_23_0.png

This shortcut also supports time step. For instance, to display the data points every 10 years between 1850 AD and 2000 AD:

[13]:

fig, ax = pobj['1850':'2000':'10'].plot(marker='o')

../_images/notebooks_pp2k-pdb-load-viz_25_0.png

Check the proxy IDs on an interactive map#

One may ask “How do I know the proxy IDs?”

A cfr.ProxyDatabase object also comes with a .plotly() method that can help us check proxy IDs on an interactive map.

The below cell cannot be rendered on a webpage, but should execute in a local Jupyter notebook. It should display an interactive map, and by hovering the mouse over each site marker, one may check the metadata of a specific site, including:

pid (proxy ID)
ptype
lat
lon

Take a try by yourself!

[14]:

pdb.plotly()

Loading and Visualization

Contents

Loading and Visualization#

Load the pseudoPAGES2k dataset with `xarray`#

Load the pseudoPAEGS2k dataset with `cfr`#

Visualize the pseudoPAGES2k dataset#

Access and visualize a specific record#

Check the proxy IDs on an interactive map#

Loading and Visualization

Contents

Loading and Visualization#

Load the pseudoPAGES2k dataset with xarray#

Load the pseudoPAEGS2k dataset with cfr#

Visualize the pseudoPAGES2k dataset#

Access and visualize a specific record#

Check the proxy IDs on an interactive map#

Load the pseudoPAGES2k dataset with `xarray`#

Load the pseudoPAEGS2k dataset with `cfr`#